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Long-term stability studies of nonlinear Hamiltonian systems require symplectic integration algorithms which are both fast and accurate. In this paper, we study a symplectic integration method wherein the symplectic map representing the…

Computational Physics · Physics 2007-05-23 Govindan Rangarajan

We give a theoretical framework of stochastic non-canonical Hamiltonian systems as well as their modified symplectic structure which is named stochastic K-symplectic structure. The framework can be applied to the study of the…

Numerical Analysis · Mathematics 2017-11-10 Jialin Hong , Lihai Ji , Xu Wang , Jingjing Zhang

Generalized Additive Runge-Kutta schemes have shown to be a suitable tool for solving ordinary differential equations with additively partitioned right-hand sides. This work develops symplectic GARK schemes for additively partitioned…

Numerical Analysis · Mathematics 2023-12-14 Michael Günther , Adrian Sandu , Kevin Schäfers , Antonella Zanna

By exploiting the error functions of explicit symplectic integrators for solving separable Hamiltonians, I show that it is possible to develop explicit, time-reversible symplectic integrators for solving non-separable Hamiltonians of the…

Computational Physics · Physics 2009-09-25 Siu A. Chin

Canonical transformation plays a fundamental role in simplifying and solving classical Hamiltonian systems. We construct flexible and powerful canonical transformations as generative models using symplectic neural networks. The model…

Statistical Mechanics · Physics 2020-04-29 Shuo-Hui Li , Chen-Xiao Dong , Linfeng Zhang , Lei Wang

This paper is devoted to the study of symplectic manifolds and their connection with Hamiltonian dynamical systems. We review some properties and operations on these manifolds and see how they intervene when studying the complete…

Symplectic Geometry · Mathematics 2019-04-03 A. Lesfari

The main purpose of this paper is to give a topological and symplectic classification of completely integrable Hamiltonian systems in terms of characteristic classes and other local and global invariants.

Differential Geometry · Mathematics 2007-05-23 Nguyen Tien Zung

Explicit symplectic integrators have been important tools for accurate and efficient approximations of mechanical systems with separable Hamiltonians. For the first time, the article proposes for arbitrary Hamiltonians similar integrators,…

Numerical Analysis · Mathematics 2016-10-19 Molei Tao

We report a few sumerical tests comparing some newly defined energy-preserving integrators and symplectic methods, using either constant and variable stepsize.

Numerical Analysis · Mathematics 2010-09-30 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

The Symplectic Pontryagin method was introduced in a previous paper. This work shows that this method is applicable under less restrictive assumptions. Existence of solutions to the Symplectic Pontryagin scheme are shown to exist without…

Numerical Analysis · Mathematics 2009-02-02 Mattias Sandberg

An explicit high-order noncanonical symplectic algorithm for ideal two-fluid systems is developed. The fluid is discretized as particles in the Lagrangian description, while the electromagnetic fields and internal energy are treated as…

Plasma Physics · Physics 2016-11-23 Jianyuan Xiao , Hong Qin , Philip J. Morrison , Jian Liu , Zhi Yu , Ruili Zhang , Yang He

We present an adaptation of the so-called structural method \cite{CMM23} for Hamiltonian systems, and redesign the method for this specific context, which involves two coupled differential systems. Structural schemes decompose the problem…

Numerical Analysis · Mathematics 2025-01-24 Stéphane Clain , Emmanuel Franck , Victor Michel-Dansac

Symplectic integration algorithms are well-suited for long-term integrations of Hamiltonian systems because they preserve the geometric structure of the Hamiltonian flow. However, this desirable property is generally lost when adaptive…

Astrophysics · Physics 2025-10-20 Miguel Preto , Scott Tremaine

In the recent years, considerable attention has been paid to preserving structures and invariants in reduced basis methods, in order to enhance the stability and robustness of the reduced system. In the context of Hamiltonian systems,…

Numerical Analysis · Mathematics 2018-03-22 Babak Maboudi Afkham , Ashish Bhatt , Bernard Haasdonk , Jan S. Hesthaven

A novel symplectic integrator for Hamiltonian equations on $S_2^n \times T^{\ast} \RR^m$ is developed and studied. Partitioned Runge--Kutta methods for Hamiltonian systems on products of Hamiltionian manifolds are studied, specifically,…

Numerical Analysis · Mathematics 2018-09-18 Geir Bogfjellmo

On this paper, we have proposed an approach to observe the time-centered difference scheme for dissipative mechanical systems from a Hamiltonian perspective and to introduce the idea of symplectic algorithm to dissipative systems. The…

Mathematical Physics · Physics 2010-08-06 Tianshu Luo , Yimu Guo

Hamilton's equations of motion form a fundamental framework in various branches of physics, including astronomy, quantum mechanics, particle physics, and climate science. Classical numerical solvers are typically employed to compute the…

Machine Learning · Computer Science 2024-10-25 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

When numerically integrating canonical Hamiltonian systems, the long-term conservation of some of its invariants, among which the Hamiltonian function itself, assumes a central role. The classical approach to this problem has led to the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

Modified Hamiltonians are used in the field of geometric numerical integration to show that symplectic schemes for Hamiltonian systems are accurate over long times. For nonlinear systems the series defining the modified Hamiltonian usually…

Numerical Analysis · Mathematics 2018-11-14 Shami A Alsallami , Jitse Niesen , Frank W Nijhoff

Though ubiquitous as first-principles models for conservative phenomena, Hamiltonian systems present numerous challenges for model reduction even in relatively simple, linear cases. Here, we present a method for the projection-based model…

Numerical Analysis · Mathematics 2024-07-12 Anthony Gruber , Irina Tezaur